Tính toán độ dịch chuyển hóa học 13C của bakuchiol‒tác nhân mới điều trị tổn thương các cơ quan

The calculations of 13C NMR chemical shifts for bakuchiol, a promising anti-aging agent, were performed using 11

functionals (B3LYP, B3PW91, BPV86, CAM-B3LYP, HCTH, HSEH1PBE, mPW1PW91, PBEPBE, TPSSTPSS, and

ωB97XD) and 10 common basis sets (3-21G, 6-31G(d,p), 6-31G(d,3p), 6-31G(3d,p) 6-31G++(d,p), DGDZVP,

DGDZVP2, LANL2DZ, LANL2MB) to compare with experimental data. While functionals did not strongly impact the

computed 13C chemical shifts, basis sets showed a significant influence on the results. For those functionals, B3LYP,

B3PW91, CAM-B3LYP, HSEH1PBE, mPW1PW91, and ωB97XD were found to have strong correlations (r2 ≥ 0.9987)

and low errors (CMAEs ≤ 1.96 ppm and CMAEs ≤ 2.49 ppm); among the tested basis sets 3-21G, DGDZVP provided

the best results (r2 ≥ 0.9980, CMAEs ≤ 2.37 ppm and CMAEs ≤ 2.67 ppm). These results would allow meaningful

predictions of 13C chemical shifts for bakuchiol

Tính toán độ dịch chuyển hóa học 13C của bakuchiol‒tác nhân mới điều trị tổn thương các cơ quan trang 1

Trang 1

Tính toán độ dịch chuyển hóa học 13C của bakuchiol‒tác nhân mới điều trị tổn thương các cơ quan trang 2

Trang 2

Tính toán độ dịch chuyển hóa học 13C của bakuchiol‒tác nhân mới điều trị tổn thương các cơ quan trang 3

Trang 3

Tính toán độ dịch chuyển hóa học 13C của bakuchiol‒tác nhân mới điều trị tổn thương các cơ quan trang 4

Trang 4

Tính toán độ dịch chuyển hóa học 13C của bakuchiol‒tác nhân mới điều trị tổn thương các cơ quan trang 5

Trang 5

Tính toán độ dịch chuyển hóa học 13C của bakuchiol‒tác nhân mới điều trị tổn thương các cơ quan trang 6

Trang 6

Tính toán độ dịch chuyển hóa học 13C của bakuchiol‒tác nhân mới điều trị tổn thương các cơ quan trang 7

Trang 7

pdf 7 trang viethung 8100
Bạn đang xem tài liệu "Tính toán độ dịch chuyển hóa học 13C của bakuchiol‒tác nhân mới điều trị tổn thương các cơ quan", để tải tài liệu gốc về máy hãy click vào nút Download ở trên

Tóm tắt nội dung tài liệu: Tính toán độ dịch chuyển hóa học 13C của bakuchiol‒tác nhân mới điều trị tổn thương các cơ quan

Tính toán độ dịch chuyển hóa học 13C của bakuchiol‒tác nhân mới điều trị tổn thương các cơ quan
Nguyen Thi Nhu Y, Nguyen Trong Thien / Tạp chí Khoa học và Công nghệ Đại học Duy Tân 02(45) (2021) 58-64 58 
 13C chemical shift predictions for bakuchiol‒a recently discovered agent 
against organ damage 
Tính toán độ dịch chuyển hóa học 13C của bakuchiol‒tác nhân mới điều trị tổn thương 
các cơ quan 
Nguyen Thi Nhu Ya, Nguyen Trong Thiena,b* 
Nguyễn Thị Như Ý a, Nguyễn Trọng Thiệna,b* 
aFaculty of Pharmacy, College of Medicine and Pharmacy Duy Tan University, Da Nang 550000, Vietnam 
bKhoa Dược, Trường Y- Dược, Đại học Duy Tân, Đà Nẵng, Việt Nam 
bInstitute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam 
bViện Nghiên cứu và Phát triển Công nghệ Cao, Đại học Duy Tân, Đà Nẵng, Việt Nam 
 (Ngày nhận bài: 03/12/2020, ngày phản biện xong: 07/01/2021, ngày chấp nhận đăng: 13/03/2021) 
Abstract 
The calculations of 13C NMR chemical shifts for bakuchiol, a promising anti-aging agent, were performed using 11 
functionals (B3LYP, B3PW91, BPV86, CAM-B3LYP, HCTH, HSEH1PBE, mPW1PW91, PBEPBE, TPSSTPSS, and 
ωB97XD) and 10 common basis sets (3-21G, 6-31G(d,p), 6-31G(d,3p), 6-31G(3d,p) 6-31G++(d,p), DGDZVP, 
DGDZVP2, LANL2DZ, LANL2MB) to compare with experimental data. While functionals did not strongly impact the 
computed 13C chemical shifts, basis sets showed a significant influence on the results. For those functionals, B3LYP, 
B3PW91, CAM-B3LYP, HSEH1PBE, mPW1PW91, and ωB97XD were found to have strong correlations (r2 ≥ 0.9987) 
and low errors (CMAEs ≤ 1.96 ppm and CMAEs ≤ 2.49 ppm); among the tested basis sets 3-21G, DGDZVP provided 
the best results (r2 ≥ 0.9980, CMAEs ≤ 2.37 ppm and CMAEs ≤ 2.67 ppm). These results would allow meaningful 
predictions of 13C chemical shifts for bakuchiol. 
Keywords: 13C chemical shifts; NMR; DFT functionals; basis sets; bakuchiol. 
Tóm tắt 
Phổ 13C của bakuchiol, tác nhân chống lão hóa, được tính toán bằng 11 hàm mật độ (B3LYP, B3PW91, BPV86, CAM-
B3LYP, HCTH, HSEH1PBE, mPW1PW91, PBEPBE, TPSSTPSS, và ωB97XD) và 10 mức lý thuyết (3-21G, 6-
31G(d,p), 6-31G(d,3p), 6-31G(3d,p) 6-31G++(d,p), DGDZVP, DGDZVP2, LANL2DZ, LANL2MB) nhằm so sánh với 
dữ liệu thực nghiệm. Trong khi các hàm mật độ thể hiện ảnh hưởng nhỏ lên độ dịch chuyển hóa học 13C, các kết quả 
tính toán bằng mức lý thuyết cho thấy sự phân hóa rộng hơn về độ chính xác. B3LYP, B3PW91, CAM-B3LYP, 
HSEH1PBE, mPW1PW91, và ωB97XD có độ tương quan cao (r2 ≥ 0.9987) và lỗi thấp (CMAEs ≤ 1.97 ppm và 
CMAEs ≤ 2.49 ppm); trong các mức lý thuyết, 3-21G, DGDZVP cho các kết quả với độ chính xác cao (r2 ≥ 0.9980, 
CMAEs ≤ 2.37 ppm and CMAEs ≤ 2.67 ppm). 
Từ khóa: Phổ 13C; NMR; hàm DFT; mức lý thuyết; bakuchiol. 
*Corresponding Author: Nguyen Trong Thien; Faculty of Pharmacy, College of Medicine and Pharmacy Duy Tan 
University, Da Nang 550000, Vietnam; Institute of Research and Development, Duy Tan University, Da Nang 550000, 
Vietnam 
Email: nguyentrongthien@duytan.edu.vn 
02(45) (2021) 58-64
Nguyen Thi Nhu Y, Nguyen Trong Thien / Tạp chí Khoa học và Công nghệ Đại học Duy Tân 02(45) (2021) 58-64 59 
1. Introduction 
 Bakuchiol (Figure 1), a prenylated phenolic 
monoterpene isolated from the fruit of Psoralea 
corylifolia, has recently shown a variety of 
pharmacological effects such as antioxidant, 
anti-bacterial, anti-inflammatory, anti-aging, 
and estrogen-like effects[1][2]. It also has 
protective effects in the heart, liver skin, and 
other organs. In addition, bakuchiol inhibits the 
proliferation of various cancer cells, including 
stomach, breast, and skin cancer cells and 
liverfibrosis via promoting myofibroblast 
apoptosis. It relieves the hepatotoxic of 
multiple toxicants by suppressing oxidative 
stress and inflammatory changes[3]. 
Understanding the structure of bakuchiol would 
provide insights into its pharmacological 
effects. 
Figure 1. (A) Bakuchiol and (B) its optimized structure at the IEFPCM(CHCl3)/B3LYP-631G(d,p) level of theory with 
numbered carbons (H atoms were omitted for clarity). 
The combination of experimental and 
computational NMR techniques has been a 
strong tool for providing the structural 
information of biologically active natural 
products, which can support the difficult 
assignments and the confirmation of their 
structures and provide valuable insights into the 
electronic environments of active NMR nucleus 
[4][5][6]. The gauge-including atomic orbitals 
(GIAO)/density functional theory (DFT) 
method are generally accepted as a standard 
method in computing shielding constants due to 
its reliability and applicability [7][8][9]. The 
accuracy of calculated chemical shifts typically 
depends on an appropriate combination of 
exchange-correlation functionals and basis sets 
[10]. Aimed to find suitable methods with high 
accuracy, this present study evaluated 11 DFT 
functionals and 11 common basis sets in the 
calculations of 13C chemical shifts for 
bakuchiol. 
2. Computational methods 
All calculations were performed using the 
Gaussian09 [11]. Geometry optimizations of 
bakuchiol were performed at the 
IEFPCM(CHCl3)/B3LYP/6-31G(d,p) level[12][13]. 
Subsequent frequency calculations ensured that 
a potential energy surface (PES) local 
minimum was attained during the energy 
minimization. Cartesian coordinates of the 
resulting structures are given in the Supporting 
Information. 
The following 11 functionals coupled with 
6-31G(d,p) [14] and 10 basis set coupled with 
B3LYP [15] were evaluated: 
- Funtionals: B3LYP (Becke’s 3-parameter 
hybrid functional[16] using B exchange[17] 
and LYP correlation),[15] B3PW91 (Perdew 
and Wang’s 1991 gradient-corrected correlation 
functional),[18][19] BPV86 (Perdew’s 1986 
functional),[16][20][21] CAM-B3LYP (Handy 
Nguyen Thi Nhu Y, Nguyen Trong Thien / Tạp chí Khoa học và Công nghệ Đại học Duy Tân 02(45) (2021) 58-64 60 
and co-workers’ long-range corrected version 
of B3LYP using the Coulomb-attenuating 
 ... viations. Overall, the 
correlation coefficients and error results 
indicate that the calculations provided a 
qualitatively accurate description of the 13C 
NMR chemical shifts. The CMAE and CRMSE 
values were in the ranges of 1.44 to 2.62 ppm 
and 1.72 to 3.53 ppm, respectively. The 
coefficients of determination (r2) were above 
0.9976 for all tested functionals. C3 and C16 
were consistently observed with the noticeable 
deviations ranged from 2.18 to 6.28 ppm and 
2.39 to 4.98 ppm, respectively (Figure 2). The 
Nguyen Thi Nhu Y, Nguyen Trong Thien / Tạp chí Khoa học và Công nghệ Đại học Duy Tân 02(45) (2021) 58-64 61 
two best performers with strong correlations 
and low errors for 13C calculations were CAM-
B3LYP (CMAE = 1.44 ppm, CRMSE = 1.72 
ppm, and r2 = 0.9991), ωB97XD (CMAE = 
1.48ppm, CRMSE = 1.80 ppm, and r2 = 0.9990). 
Table 1. 13C NMR chemical shifts of bakuchiol calculated using 11 functionals 
δ(13C) 
Entry 
Functional 
r2 CMAE CRMSE 
1 
B3LYP 
0.9987 1.79 2.33 
2 
B3PW91 
0.9988 1.97 2.49 
3 
BPV86 
0.9978 2.36 3.17 
4 
CAM-B3LYP 0.9991 1.44 1.72 
5 
HCTH 
0.9981 2.23 2.96 
6 
HSEH1PBE 0.9989 1.91 2.34 
7 
LSDA 
0.9976 2.62 3.53 
8 
mPW1PW91 0.9989 1.91 2.36 
9 
PBEPBE 
0.9989 1.91 2.34 
10 
TPSSTPSS 0.9981 2.50 2.94 
11 ωB97XD 0.9990 1.48 1.80 
Figure 2. Absolute deviations of 13C chemical shift calculations using 11 functionals. 
3.2. The evaluation of 11 basis sets 
11 Basic sets were employed for computing 
13C chemical shifts of bakuchiol. In general, the 
calculated results were observed with low 
associated errors and strong linear correlations 
(r2 ≥ 0.9958). CMAE and CRMSE values were 
ranged from 1.79 to 4.97 ppm and 2.22 to 5.13 
ppm, respectively (Table 3). The largest 
deviations were found for C3, C11, and C16 
with CMAE and CRMSE values in the ranges 
of 1.05 to 6.25 ppm, 0.46 to 6.11 ppm, and 2.13 
to 4.47 ppm, respectively (Figure 1). 
Nguyen Thi Nhu Y, Nguyen Trong Thien / Tạp chí Khoa học và Công nghệ Đại học Duy Tân 02(45) (2021) 58-64 62 
Table 2. The calculated 13C NMR chemical shifts of Bakuchiol in CHCl3 using 10 basic sets. 
All chemical shifts, CMAEs, and CRMSEs are in ppm. 
 δ(
13C) 
Entry Basis set r
2 CMAE CRMSE 
1 3-21G 0.9981 2.37 2.67 
2 6-31G(d,p) 0.9987 1.79 2.33 
3 6-31G(3d,p) 0.9971 2.62 3.21 
4 6-31G(d,3p) 0.9975 2.33 2.67 
5 6-31++G(d,p) 0.9958 3.35 3.43 
6 6-311G 0.9976 1.93 2.71 
7 DGDZVP 0.9985 2.19 2.22 
8 DGDZVP2 0.9962 4.97 5.13 
10 LANL2DZ 0.9970 3.13 3.28 
11 LANL2MB 0.9970 3.80 3.81 
Figure 3. Absolute deviations of 13C chemical shift calculations using 10 basis sets. 
4. Conclusion 
We have performed the evaluation of 11 
DFT functionals and 11 basis sets using GIAO 
method on the calculation of 13C chemical 
shifts for bakuchiol. Our results showed the two 
best performing functionals were CAM-B3LYP 
(CMAEs ≤ 1.44 ppm) and ωB97XD (CRMSEs 
≤ 1.80 ppm), and the best basis set was 6-
31G(d,p) (CMAEs ≤ 1.79 ppm). In these cases, 
excellent correlations between theoretical and 
experimental data (r2 > 0.9987) were observed. 
Given such high degree of accuracy achieved in 
calculating 13C chemical shifts of bakuchiol, 
this work can be useful for supporting the 
assignments of the experimental NMR spectra of 
bakuchiol and similar retinoid compounds. 
Further studies on the chemical shift calculations 
of these compounds are under-investigation. 
Nguyen Thi Nhu Y, Nguyen Trong Thien / Tạp chí Khoa học và Công nghệ Đại học Duy Tân 02(45) (2021) 58-64 63 
References 
[1] S. Dhaliwal, I. Rybak, S.R. Ellis, M. Notay, M. 
Trivedi, W. Burney, A.R. Vaughn, M. Nguyen, P. 
Reiter, S. Bosanac, H. Yan, N. Foolad, R.K. 
Sivamani, Prospective, randomized, double‐blind 
assessment of topical bakuchiol and retinol for 
facial photoageing, Br. J. Dermatol. 180 (2019) 
289–296. https://doi.org/10.1111/bjd.16918. 
[2] T. Esumi, C. Yamamoto, Y. Fukuyama, A short 
synthesis of (+)-bakuchiol, Synlett. 24 (2013) 1845–
1847. https://doi.org/10.1055/s-0033-1338968. 
[3] Z. Xin, X. Wu, T. Ji, B. Xu, Y. Han, M. Sun, S. 
Jiang, T. Li, W. Hu, C. Deng, Y. Yang, Bakuchiol: 
A newly discovered warrior against organ damage, 
Pharmacol. Res. 141 (2019) 208–213. 
https://doi.org/10.1016/j.phrs.2019.01.001. 
[4] H.D. Watts, M.N.A. Mohamed, J.D. Kubicki, 
Comparison of multistandard and TMS-standard 
calculated NMR shifts for coniferyl alcohol and 
application of the multistandard method to lignin 
dimers, J. Phys. Chem. B. 115 (2011) 1958–1970. 
https://doi.org/10.1021/jp110330q. 
[5] J.S. Lomas, 1 H NMR spectra of alcohols and diols 
in chloroform: DFT/GIAO calculation of chemical 
shifts, Magn. Reson. Chem. 52 (2014) 745–754. 
https://doi.org/10.1002/mrc.4130. 
[6] B.G. Diehl, H.D. Watts, J.D. Kubicki, M.R. Regner, 
J. Ralph, N.R. Brown, Towards lignin-protein 
crosslinking: Amino acid adducts of a lignin model 
quinone methide, Cellulose. 21 (2014) 1395–1407. 
https://doi.org/10.1007/s10570-014-0181-y. 
[7] K. Wolinski, J.F. Hinton, P. Pulay, Efficient 
Implementation of the Gauge-Independent Atomic 
Orbital Method for NMR Chemical Shift 
Calculations, J. Am. Chem. Soc. 112 (1990) 8251–
8260. https://doi.org/10.1021/ja00179a005. 
[8] J. Gauss, Effects of electron correlation in the 
calculation of nuclear magnetic resonance chemical 
shifts, J. Chem. Phys. 99 (1993) 3629–3643. 
https://doi.org/10.1063/1.466161. 
[9] R. Ditchfield, Self-consistent perturbation theory of 
diamagnetism I. A gauge-invariant LCAO method 
for N.M.R. Chemical shifts, Mol. Phys. 27 (1974) 
789–807. 
https://doi.org/10.1080/00268977400100711. 
[10] M.A. Iron, Evaluation of the Factors Impacting the 
Accuracy of 13C NMR Chemical Shift Predictions 
using Density Functional Theory - The Advantage 
of Long-Range Corrected Functionals, J. Chem. 
Theory Comput. 13 (2017) 5798–5819. 
https://doi.org/10.1021/acs.jctc.7b00772. 
[11] M.J. Frisch, J.R. Cheeseman, G. Scalmani, V. 
Barone, B. Mennucci, G.A. Petersson, H. Nakatsuji, 
M. Caricato, X. Li, H.P. Hratchian, A.F. Izmaylov, 
J. Bloino, G. Zheng, J.L. Sonnenberg, M. Hada, M. 
Ehara, K. Toyota, R. Fukuda, J. Hasegawa, M. 
Ishida, T. Nakajima, Y. Honda, O. Kitao, H. Nakai, 
T. Vreven, J.A. Montgomery Jr., J.E. Peralta, F. 
Ogliaro, M. Bearpark, J.J. Heyd, E. Brothers, K.N. 
Kudin, V.N. Staroverov, T. Keith, R. Kobayashi, J. 
Normand, K. Raghavachari, A. Rendell, J.C. Burant, 
S.S. Iyengar, J. Tomasi, M. Cossi, N. Rega, J.M. 
Millam, M. Klene, J.E. Knox, J.B. Cross, V. 
Bakken, C. Adamo, J. Jaramillo, R. Gomperts, R.E. 
Stratmann, O. Yazyev, A.J. Austin, R. Cammi, C. 
Pomelli, J.W. Ochterski, R.L. Martin, K. 
Morokuma, V.G. Zakrzewski, G.A. Voth, P. 
Salvador, J.J. Dannenberg, S. Dapprich, A.D. 
Daniels, O. Farkas, J.B. Foresman, J. V. Ortiz, J. 
Cioslowski, F.D. J., Gaussian 09, Revision D.01, 
(2013). 
[12] J. Tomasi, B. Mennucci, R. Cammi, Quantum 
mechanical continuum solvation models, Chem. 
Rev. 105 (2005) 2999–3093. 
 https://doi.org/10.1021/cr9904009. 
[13] J. Tomasi, B. Mennucci, E. Cancès, The IEF version 
of the PCM solvation method: An overview of a 
new method addressed to study molecular solutes at 
the QM ab initio level, in: J. Mol. Struct. 
THEOCHEM, Elsevier, 1999: pp. 211–226. 
https://doi.org/10.1016/S0166-1280(98)00553-3. 
[14] M.M. Francl, W.J. Pietro, W.J. Hehre, J.S. Binkley, 
M.S. Gordon, D.J. DeFrees, J.A. Pople, Self-
consistent molecular orbital methods. XXIII. A 
polarization-type basis set for second-row elements, 
J. Chem. Phys. 77 (1982) 3654–3665. 
https://doi.org/10.1063/1.444267. 
[15] P.J. Stephens, F.J. Devlin, C.F. Chabalowski, M.J. 
Frisch, Ab Initio calculation of vibrational 
absorption and circular dichroism spectra using 
density functional force fields, J. Phys. Chem. 98 
(1994) 11623–11627. 
 https://doi.org/10.1021/j100096a001. 
[16] A.D. Becke, Density-functional thermochemistry. 
III. The role of exact exchange, J. Chem. Phys. 98 
(1993) 5648–5652. 
https://doi.org/10.1063/1.464913. 
[17] A.D. Becke, Density-functional exchange-energy 
approximation with correct asymptotic behavior, 
Phys. Rev. A. 38 (1988) 3098–3100. 
https://doi.org/10.1103/PhysRevA.38.3098. 
[18] J.P. Perdew, J.A. Chevary, S.H. Vosko, K.A. 
Jackson, M.R. Pederson, D.J. Singh, C. Fiolhais, 
Atoms, molecules, solids, and surfaces: 
Applications of the generalized gradient 
approximation for exchange and correlation, Phys. 
Rev. B. 46 (1992) 6671–6687. 
 https://doi.org/10.1103/PhysRevB.46.6671. 
[19] J.P. Perdew, J.A. Chevary, S.H. Vosko, K.A. 
Jackson, M.R. Pederson, D.J. Singh, C. Fiolhais, 
Erratum: Atoms, molecules, solids, and surfaces: 
Nguyen Thi Nhu Y, Nguyen Trong Thien / Tạp chí Khoa học và Công nghệ Đại học Duy Tân 02(45) (2021) 58-64 64 
Applications of the generalized gradient 
approximation for exchange and correlation 
(Physical Review B (1993) 48, 7, (4978)), Phys. 
Rev. B. 48 (1993) 4978. 
 https://doi.org/10.1103/PhysRevB.48.4978.2. 
[20] J.P. Perdew, Density-functional approximation for 
the correlation energy of the inhomogeneous 
electron gas, Phys. Rev. B. 33 (1986) 8822–8824. 
https://doi.org/10.1103/PhysRevB.33.8822. 
[21] S.H. Vosko, L. Wilk, M. Nusair, Accurate spin-
dependent electron liquid correlation energies for 
local spin density calculations: a critical analysis, 
Can. J. Phys. 58 (1980) 1200–1211. 
https://doi.org/10.1139/p80-159. 
[22] T. Yanai, D.P. Tew, N.C. Handy, A new hybrid 
exchange-correlation functional using the Coulomb-
attenuating method (CAM-B3LYP), Chem. Phys. 
Lett. 393 (2004) 51–57. 
 https://doi.org/10.1016/j.cplett.2004.06.011. 
[23] F.A. Hamprecht, A.J. Cohen, D.J. Tozer, N.C. 
Handy, Development and assessment of new 
exchange-correlation functionals, J. Chem. Phys. 
109 (1998) 6264–6271. 
 https://doi.org/10.1063/1.477267. 
[24] A. Daniel Boese, N.L. Doltsinis, N.C. Handy, M. 
Sprik, New generalized gradient approximation 
functionals, J. Chem. Phys. 112 (2000) 1670–1678. 
https://doi.org/10.1063/1.480732. 
[25] A.D. Boese, N.C. Handy, A new parametrization of 
exchange-correlation generalized gradient 
approximation functionals, J. Chem. Phys. 114 
(2001) 5497–5503. 
 https://doi.org/10.1063/1.1347371. 
[26] J. Heyd, G.E. Scuseria, M. Ernzerhof, Hybrid 
functionals based on a screened Coulomb potential, 
J. Chem. Phys. 118 (2003) 8207–8215. 
https://doi.org/10.1063/1.1564060. 
[27] M. Ernzerhof, J.P. Perdew, Generalized gradient 
approximation to the angle- and system-averaged 
exchange hole, J. Chem. Phys. 109 (1998) 3313–
3320. https://doi.org/10.1063/1.476928. 
[28] J.P. Perdew, Y. Wang, Accurate and simple analytic 
representation of the electron-gas correlation 
energy, Phys. Rev. B. 45 (1992) 13244–13249. 
https://doi.org/10.1103/PhysRevB.45.13244. 
[29] J.P. Perdew, K. Burke, Generalized gradient 
approximation for the exchange-correlation hole of 
a many-electron system, Phys. Rev. B - Condens. 
Matter Mater. Phys. 54 (1996) 16533–16539. 
https://doi.org/10.1103/PhysRevB.54.16533. 
[30] C. Adamo, V. Barone, Exchange functionals with 
improved long-range behavior and adiabatic 
connection methods without adjustable parameters: 
The mPW and mPW1PW models, J. Chem. Phys. 
108 (1998) 664–675. 
 https://doi.org/10.1063/1.475428. 
[31] J.P. Perdew, K. Burke, M. Ernzerhof, Generalized 
gradient approximation made simple, Phys. Rev. 
Lett. 77 (1996) 3865–3868. 
 https://doi.org/10.1103/PhysRevLett.77.3865. 
[32] J. Tao, J.P. Perdew, V.N. Staroverov, G.E. Scuseria, 
Climbing the density functional ladder: 
Nonempirical meta–generalized gradient 
approximation designed for molecules and solids, 
Phys. Rev. Lett. 91 (2003) 146401. 
 https://doi.org/10.1103/PhysRevLett.91.146401. 
[33] J.P. Perdew, A. Ruzsinszky, G.I. Csonka, L.A. 
Constantin, J. Sun, Workhorse semilocal density 
functional for condensed matter physics and quantum 
chemistry, Phys. Rev. Lett. 103 (2009) 026403. 
https://doi.org/10.1103/PhysRevLett.103.026403. 
[34] J. Da Chai, M. Head-Gordon, Systematic 
optimization of long-range corrected hybrid density 
functionals, J. Chem. Phys. 128 (2008) 084106. 
https://doi.org/10.1063/1.2834918. 
[35] J. Chai, M. Head-Gordon, Long-range corrected 
hybrid density functionals with damped atom–atom 
dispersion corrections, Phys. Chem. Chem. Phys. 10 
(2008) 6615–6620. 
 https://doi.org/10.1039/B810189B. 
[36] J. Stephen Binkley, J. A. Pople, W. J. Hehre, Self-
consistent molecular orbital methods. 21. Small 
split-valence basis sets for first-row elements, J. 
Am. Chem. Soc. 102 (1980) 939–947. 
 https://doi.org/10.1021/ja00523a008. 
[37] R. Ditchfield, W.J. Hehre, J.A. Pople, Self-
consistent molecular-orbital methods. IX. An 
extended gaussian-type basis for molecular-orbital 
studies of organic molecules, J. Chem. Phys. 54 
(1971) 720–723. https://doi.org/10.1063/1.1674902. 
[38] C. Sosa, J. Andzelm, B. C. Elkin, E. Wimmer, K. D. 
Dobbs, D. A. Dixon, A local density functional 
study of the structure and vibrational frequencies of 
molecular transition-metal compounds, J. Phys. 
Chem. 96 (1992) 6630–6636. 
 https://doi.org/10.1021/j100195a022. 
[39] P.J. Hay, W.R. Wadt, Ab initio effective core 
potentials for molecular calculations. Potentials for 
the transition metal atoms Sc to Hg, J. Chem. Phys. 
82 (1985) 270–283. 
 https://doi.org/10.1063/1.448799. 
[40] W.R. Wadt, P.J. Hay, Ab initio effective core 
potentials for molecular calculations. Potentials for 
main group elements Na to Bi, J. Chem. Phys. 82 
(1985) 284–298. https://doi.org/10.1063/1.448800. 
[41] T.T. Nguyen, P.Q. Le, J. Helminen, J. Sipilä, The 
1H and 13C chemical shifts of 5–5 lignin model 
dimers: An evaluation of DFT functionals, J. Mol. 
Struct. 1226 (2021) 129300. 
 https://doi.org/10.1016/j.molstruc.2020.129300. 

File đính kèm:

  • pdftinh_toan_do_dich_chuyen_hoa_hoc_13c_cua_bakuchioltac_nhan_m.pdf